Radar systems are used in motor vehicles for a variety of purposes, such as navigation display, collision avoidance warning, automatic cruise control adjustment, automatic braking, and automatic steering. In a moving vehicle, virtually all objects are moving with respect to the host vehicle. Other vehicles traveling in the same direction may appear to be moving relatively slowly, while oncoming traffic appears to be moving much more rapidly. Vehicles change speed and turn unpredictably while stationary or slow moving objects, such as hazards and pedestrians, may appear on the side of the road or in the roadway. Objects often become temporarily obstructed by other objects only to appear suddenly in the field of view. Objects moving at different speeds therefore continually come into and out of the radar's field of view in an unpredictable way in the ordinary course of driving. This presents a challenging situation for automotive radar systems implementing automated object detection, classification, threat detection and response.
Image deblurring is an important aspect of radar image processing in automotive radar systems. Image deblurring techniques are generally more effective when additional information about the image, often referred to as “priors,” is available to augment the raw radar data. For example, prior information regarding the boundaries of objects in the image moving at different speeds can be utilized to greatly enhance image deblurring using known techniques. Unfortunately, automotive radar data is usually provided with “weak priors” meaning that little or no information is available regarding the content of the image prior to image processing. Deblurring of images including multiple objects moving at different speeds with “weak priors” is therefore known to be a challenging problem. The challenge is exacerbated in an automotive radar system, in which virtually all of the objects are moving at different relative speeds and often become temporarily obscured while passing through the field of view.
Accordingly, it is desirable to provide an improved radar image processing system for deblurring radar images with “weak priors” in automotive radar systems. More specifically, there is a need for object boundary detection techniques for use in subsequent image deblurring, object detection and response in automotive radar systems.